As AI models advance, companies are showing growing interest in autonomous AI agents that can carry out tasks without people. Yet complaints persist that AI-driven automation is still slow, even in Silicon Valley, highlighting a gap between expectations and on-the-ground experience. Some argue today’s large language models are built to assist humans rather than automate work, and that pursuing both goals can produce uneven performance. Surveys cited in reports show time saved by AI is often spent fixing or checking AI outputs.

Moves by major technology companies targeting local, on-device AI that runs on standard hardware are accelerating, with Microsoft joining Nvidia in an aggressive push. Microsoft unveiled a new Surface Laptop Ultra with Nvidia AI chips and highlighted “hybrid intelligence” that splits AI work between PCs and the cloud. Nvidia introduced a 64GB DGX Spark configuration. Competition is also intensifying in personal AI agents, as startups raise funding and companies roll out new models, platforms and acquisitions.